(1) Field of the Invention
The invention relates to a method for evaluating fluorescence measurement data in at least one-dimensional spatial resolution from a sample and a control unit for a laser scanning microscope.
(2) Description of Related Art Including Information Disclosed Under 37 CFR 1.97 and 1.98
Fluorescence correlation spectroscopy (FCS) can be used to examine variable substance concentrations in the microscopic range caused by diffusion and other transport processes in a sample. Physical and biological transport processes in or through a single volume having a diameter of about 200 nm can be observed in this way. Spatial resolution of microscopic transport processes is achieved by scanning fluorescence correlation spectrography (S-FCS), also referred to as image correlation spectroscopy (ICS). Time spans of seconds to minutes can be tracked.
Raster image correlation spectroscopy (RICS) allows tracking within a cell or between cells separated by a membrane in the microsecond and millisecond range in two or three-dimensional spatial resolution (Digman et al.: “Measuring Fast Dynamics in Solutions and Cells with a Laser Scanning Microscope” in “Biophysical Journal”, Vol. 89, August 2005, pp. 1317-1327). The sample is optically scanned here in a two or three-dimensional grid. In the typical process, time series are recorded. It is advantageous to use a laser scanning microscope (LSM) for scanning correlation spectroscopy. During the optical scanning movement of a RICS measurement, digital sampling values are electronically recorded at a typically constant sampling frequency and further processed into pixel values. Each pixel value is determined from one or multiple sampling values. Scanning along the first scan direction is repeated along a second scan direction after the scanning beam has been shifted (scan gap) such that a series of pixel rows is recorded.
To be able to make statements about transport processes in a sample, correlation-spectroscopic measuring procedures are typically evaluated by determining correlations of the fluorescence measurement data such as auto or cross-correlations and by adapting mathematical transport models to these correlations, for example, by means of curve fittings. The adjusted models can be used to determine sample properties such as diffusion constants. The transport models are available in the form of mathematical functions, and the parameters of these functions are adjusted. Such correlation analyses with respect to RICS measurements are performed separately for several, typically overlapping, regions of the scan field. The determination of model parameters in each region, i.e. the determination of the spatial distribution of the model parameters within the sample, is called mapping. The results of correlation analyses can be presented graphically, e.g. using false colors.
It is a problem that areas can be contained in one or several sample regions that contain little or no information and therefore falsify the results of the analysis. For example, these can be dark, almost fluorescence-free areas in which noise is detected at best. It is possible in areas of low fluorescence that a correlation of measurement data of the corresponding sample region cannot be evaluated for lack of statistics. If sample properties such as a diffusion constant are determined in such sample regions despite their low information content, adapting the parameters of a model function by curve fitting will result in absurd values for the desired sample properties despite good adjustment quality. Values could be obtained for a diffusion constant that is too high by several orders of magnitude.
It is known from prior art that faulty fluorescence correlation analyses can be filtered out by comparing the adapted model function parameters, that is, the results of the curve fittings, to meaningful ranges of values. If the results are outside these ranges of values, they are discarded and not used for determining the desired sample properties. In addition to restricting the values to ranges, it is known to discard the results of curve fittings if the mean value deviations of the model function parameters exceed a preset threshold or if the ratio of the standard deviations of the model function parameters to their best values exceeds a predetermined threshold. All approaches listed above have the disadvantage that the meaningful ranges of values or the threshold values, respectively, have to be determined as so-called a priori knowledge in time-consuming test series. The rigid limitation to a specific range of values or thresholds diminishes the accuracy of the evaluation since statistically correct correlations that result in model parameter values outside the limits will be discarded. In addition, one or, if several sample regions are mapped, multiple elaborate and time-consuming curve fittings have to be performed before the results can be checked for meaningfulness.
The problem to be addressed by the invention therefore is that of providing a method and control unit of the types mentioned above with the help of which sample properties can be determined from fluorescence correlations in a simpler, faster and more accurate way.